A AREVA Seabrook Station Unit I Fixed Incore Detector System Analysis Supplement to YAEC-1 855PA ANP-3243NP Revision 1 Licensing Report May 2014 AREVA Inc. (c) 2014 AREVA Inc.
AAREVA
Seabrook Station Unit I Fixed IncoreDetector System Analysis Supplementto YAEC-1 855PA
ANP-3243NPRevision 1
Licensing Report
May 2014
AREVA Inc.
(c) 2014 AREVA Inc.
Copyright © 2014
AREVA Inc.All Rights Reserved
AREVA Inc. ANP-3243NPRevision 1
Seabrook Station Unit 1 Fixed Incore Detector System Analysis Supplement to YAEC-1855PALicensinq Report Paqe i
Nature of Changes
Section(s)Item or Page(s) Description and Justification1 Abstract Discuss new uncertainty analysis
Section 1.1Section 5.3Section 6.2Section 7.0Appendix B
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Contents
Paqe
1.0 TECHNICAL EVALULATIO N ................................................................................ 1
1.1 Background ............................................................................................. 1
2.0 NEUTRO N CO NVERSIO N FACTO R .............................................................. 4
2.1 Current Licensing Basis .......................................................................... 4
2.2 Proposed M ethod ................................................................................. 6
3.0 REPLACEM ENT DETECTO RS ........................................................................ 8
3.1 General ................................................................................................... 8
3.2 Current Licensing Basis .......................................................................... 9
3.3 Proposed M odification ........................................................................... 9
4.0 DEPLETIO N CO RRECTIO N FACTO R .......................................................... 11
4.1 Current Licensing Basis ....................................................................... 11
4.2 Proposed M odification ......................................................................... 11
5.0 CO M PARISO N O F FINC RESULTS ............................................................... 12
5.1 General ................................................................................................. 12
5.2 Surveillance Param eter Com parisons ................................................... 12
5.3 Statistical Results ............................................................................... 26
6.0 UNCERTAINTY ANALYSIS ............................................................................ 27
6.1 Current Licensing Basis ....................................................................... 27
6.2 Proposed Uncertainty M odifications .................................................... 306.2.1 Overview .................................................................................... 306.2.2 M ethodology ............................................................................. 316.2.3 Uncertainty Calculation Details .................................................. 366.2.4 Uncertainty Calculation Results ................................................ 386.2.5 Analysis of Significant Trends .................................................. 42
7.0 CO NCLUSIO NS ............................................................................................ 46
8.0 REFERENCES ............................................................................................... 47
APPENDIX A ................................................................................................................. 48
APPENDIX B ................................................................................................................. 71
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List of Tables
Table 1 Uncertainty Components and Confidence Multipliers from YAEC-18 5 5 P A .................................................. .......................................... . . 2 9
Table 2 95/95 Uncertainty Limits for FAH and FQ ............................ . . . . . . . . . . . . . . . . . . . . . . . . . . 43
Table B-1 Conservative Trend Slope of FAH UL(95/95) and FQ UL(95/95) for aMaximum of 8 Failed Detector Strings .................................................. 75
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List of Figures
Figure 1 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 1 .................... 14
Figure 2 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 2 .................... 14
Figure 3 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 3 .................... 15
Figure 4 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 4 .................... 15
Figure 5 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 5 .................... 16
Figure 6 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 6 .................... 16
Figure 7 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 7 .................... 17
Figure 8 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 8 .................... 17
Figure 9 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 1 ........ 18
Figure 10 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 2 ....... 18
Figure 11 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 3 ....... 19
Figure 12 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 4 ....... 19
Figure 13 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 5 .......... 20
Figure 14 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 6 .......... 20
Figure 15 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 7 .......... 21
Figure 16 Comparison of Enthalpy Rise Hot Channel Factor FAH for Cycle 8 .......... 21
Figure 17 Comparison of Axial Offset for Cycle 1 ................................................... 22
Figure 18 Comparison of Axial Offset for Cycle 2 ................................................... 22
Figure 19 Comparison of Axial Offset for Cycle 3 ................................................... 23
Figure 20 Comparison of Axial Offset for Cycle 4 ................................................... 23
Figure 21 Comparison of Axial Offset for Cycle 5 ................................................... 24
Figure 22 Comparison of Axial Offset for Cycle 6 ................................................... 24
Figure 23 Comparison of Axial Offset for Cycle 7 ................................................... 25
Figure 24 Comparison of Axial Offset for Cycle 8 ................................................... 25
Figure 25 Flow Diagram of Calculations .................................................................. 35
Figure 26 FAH UL(95/95) Plots for Cycle 14, FAH Near Maximum ........................... 44
Figure 27 FQ UL(95/95) Plots for Cycle 14, FAH Near Maximum ............................. 45
Figure A-1 Measured Signal Divided by Detector Power versus DetectorExposure, O riginal Detectors ............................................................... 55
Figure A-2 Measured Signal Divided by Detector Power versus DetectorExposure, Replacement Detectors ...................................................... 56
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Figure A-3 Calculated Gamma Signal Divided by Detector Power versusDetector Exposure, Original Detectors ................................................ 57
Figure A-4 Calculated Gamma Signal Divided by Detector Power versusDetector Exposure, Replacement Detectors ........................................ 58
Figure A-5 Inferred Neutron Signal Divided by Detector Power versus DetectorExposure, O riginal Detectors ............................................................... 59
Figure A-6 Inferred Neutron Signal Divided by Detector Power versus DetectorExposure, Replacement Detectors ...................................................... 60
Figure A-7 Neutron Conversion Factor versus Detector Exposure, OriginalD e te cto rs ........................................................................................... . . 6 1
Figure A-8 Neutron Conversion Factor versus Detector Exposure, ReplacementD e te cto rs ........................................................................................... . . 6 2
Figure A-9 Calculated Gamma Divided by Measured Signal versus DetectorExposure, O riginal Detectors ............................................................... 63
Figure A-10 Calculated Gamma Divided by Measured Signal versus DetectorExposure, Replacement Detectors ...................................................... 64
Figure A-1 1 Depletion Correction Factor .................................................................. 65
Figure A-12 Difference between Predicted and Measured Signals, OriginalDetectors, Proposed M odel ................................................................. 66
Figure A-13 Difference between Predicted and Measured Signals, ReplacementDetectors, Proposed M odel ................................................................. 67
Figure A-14 Ratio of Measured Signals for Original to Replacement Detectors,B atch 1, C ycle 14 .............................................................................. . . 68
Figure A-15 Ratio of Measured Signals for Original to Replacement Detectors,B atch 1, C ycle 15 .............................................................................. . . 69
Figure A-16 Ratio of Measured Signals for Original to Replacement Detectors,B atch 2 , C ycle 15 .............................................................................. . . 70
Figure B-1 Example Linear Least Square Fits of FAH (UL 95/95) and FQ (UL 95/95) ........ 76
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Nomenclature
(If applicable)
AcronymFAH
FdhFQFIDSNCFGCFDPCST
SGSMCyOTh
lOTh avg
RnCn
CdERMS2D3DOa
Ob
Oc
Od
Ot
Ork
DefinitionEnthalpy rise hot channel factorSame as FAH; nomenclature used in YAEC-1855PAHeat flux hot channel factorFixed Incore Detector SystemNeutron Conversion FactorGamma Correction FactorDepletion Correction FactorTotal calculated detector signalCalculated detector signal due to gammaMeasured signalUnit conversion factor for calculated detector gamma signalThermal neutron fluxAverage thermal neutron fluxNeutron reaction rate for Pt-1 95Same as NCFCoefficient of DPC versus detector exposureDetector exposureRoot Mean SquareTwo-dimensionalThree-dimensionalStandard deviation for signal reproducibilityStandard deviation for analytical methodsStandard deviation for axial power shapeStandard deviation for detector processingStandard deviation for integral detector processingStandard deviation for total system (3D)Standard deviation for integral processing (2D)Confidence interval multiplier
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ABSTRACT
This document provides modifications to the Fixed Incore Detector System (FIDS)
Analysis methodology described in YAEC-1855PA. The FIDS Analysis methodology
has been in use at Seabrook Station to monitor core power distribution surveillance
parameters since Cycle 5 in 1995. The FIDS uses fixed platinum detectors which are
predominantly gamma sensitive and have a contribution from neutron capture. The
FIDS has operated successfully for over 20 years of operation. In 2007, Seabrook
undertook a phased detector replacement project. The Seabrook specification for
replacement detectors was written to produce a like-for-like replacement of the original
detectors. However, changes in manufacturing techniques required changes to the
FIDS Analysis methodology to incorporate correction factors to normalize the
replacement and the original detector signals to the standard detector performance
required by the analysis methodology. Two replacement detector strings were installed
in Cycle 14 and three detector strings were installed in Cycle 15. During Cycle 16,
Seabrook undertook a program to trend detector performance over the 15 cycles of
operation to determine appropriate modifications to the Fixed Incore Detector Code
(FINC).
Based on the trending analysis, revisions were made to the FIDS Analysis
methodology. The modifications include a more precise method to determine the
detector neutron conversion factor to better predict the neutron portion of the fixed
detector signal based on the predicted neutron reaction rate. Modifications were also
made to track detector exposure and to make a depletion correction to the measured
signal based on the detector exposure. To normalize the replacement and original
detectors, correction factors were quantified and incorporated as a multiplier on the
measured signal of the replacement detectors.
The FINC code was modified to incorporate the revised FIDS Analysis methodology and
the proposed modifications were used to rerun all 15 cycles of flux maps.
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The measurement of a core power distribution is built upon a series of comparisons
between measured incore signals and predicted incore signals in instrumented locations
of the core, and expansion of the resultant power distribution data to uninstrumented
locations. In YAEC-1855PA the uncertainty for detector processing is calculated by
comparing detector signals measured at various core conditions to predictions of the
detector signals at these same core conditions. While the FIDS uncertainty based on
the difference between measured and predicted detector signals is conservatively
bounding, it is not a good representation of the true measurement uncertainty. The
YAEC-1855PA uncertainty analysis is replaced by a method that propagates the
uncertainties through the FIDS analysis system using a Monte Carlo statistical
simulation and determines a better representation of the true measurement uncertainty
for FQ and FAH over a wide range of conditions. This uncertainty analysis methodology
is similar to that employed by the Reference 5 and 6 core power distribution monitoring
systems previously reviewed and approved by the NRC.
This report describes the detector performance trending analysis of the 15 cycles,
documents the proposed modifications to the FIDS Analysis methodology and provides
a new determination of the resulting measurement uncertainty for the FQ and FAH
Technical Specifications (Tech Specs) surveillance parameters.
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1.0 TECHNICAL EVALULATION
1.1 Background
Seabrook Station started Cycle 1 with a combination fixed/movable detector system in
58 locations within the reactor core. The Detector Assemblies at that time
accommodated the movable incore detector path, the qualified core exit thermocouple,
and the five fixed platinum incore detectors. The movable detector system was used
during the first four cycles of operation and was also used to benchmark the fixed
platinum incore detectors. The fixed detector system was licensed by the NRC during
Cycle 3 using the methodology described in YAEC-1855PA (Reference 1). The fixed
platinum incore detectors and the methodology described in YAEC-1855PA have been
used exclusively to monitor the core since Cycle 5.
YAEC-1855PA describes the methodology and uncertainty analysis used to determine
the measured core power distribution using the fixed incore detectors and the
associated uncertainty. The fixed incore detectors are self-powered platinum detectors
which are predominantly gamma sensitive and produce a signal proportional to the local
gamma flux in the reactor core. Although the majority of the signal from the platinum
detectors is derived from the gamma flux, a portion of the signal is due to the neutron
flux from an n,y reaction. There are 58 incore detector assemblies distributed radially
throughout the core. Each assembly contains 5 individual fixed incore detectors
uniformly spaced axially along the height of the core. Thus, a total of 290 detectors are
providing continuous core power distribution information. The detector signals are
scanned once per minute and stored such that they may be retrieved and analyzed to
determine the three dimensional power distribution and associated Tech Spec
surveillance parameters. The computer software package used to analyze the fixed
incore detector signals to determine the power distribution parameters is referred to as
S3FINC and is described in YAEC-1855PA.
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S3FINC has two major components. The first is the predictive codes CASMO-3
(Reference 2) for cross section generation and gamma response and SIMULATE-3
(Reference 3) for predicting the core power distribution and individual detector
responses. The second is the Fixed Incore Detector Code (FINC) which uses the
SIMULATE-3 output and measured fixed incore detector signals to determine the
measured core power distribution.
Included in YAEC-1855PA is a discussion on how the detector signals are treated as
inputs to the methodology. Important points to note from YAEC-1855PA are:
* The use of the CASMO-3/SIMULATE-3 for power distribution prediction
* The use of a standard detector approach for power distribution analysis
* The assumption that 25% of the signal is due to neutrons
* The overall uncertainty analysis for use with Tech Specs surveillance of FQ and FAH.
Although not specifically addressed in YAEC-1855PA, detectors need to be replaced
due to long term wear on the high pressure seals and signal connectors. To this extent,
Seabrook has a prototype Replacement Project to replace Detector Assemblies starting
with the OR13 (Cycle 14) refueling outage. Two detectors were replaced during OR13
and three were replaced during OR14 (Cycle 15). Seabrook has also embarked on a
program to analyze data from the first 15 cycles of operation to quantify trends in the
detector performance data and to validate the uncertainty analysis presented in YAEC-
1855PA. This topical report serves as a supplement to YAEC-1 855PA. The changes
proposed are:
* An improved prediction of the neutron component of the detector signal - Neutron
Conversion Factor (NCF),
* Applying correction factors to the measured detector signal of the replacement
detectors to better assure normalization to a standard detector performance -
Gamma Correction Factor (GCF),
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* Accounting and correcting the measured detector signal for detector depletion to
better assure normalization to a standard detector performance - Depletion
Correction (DPC), and
* Replacing the uncertainty analysis with a new analysis that better represents the
true measurement uncertainty for FQ and FAH over a wide range of conditions by
propagating the uncertainties through the FIDS analysis system using a Monte Carlo
statistical simulation method.
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2.0 NEUTRON CONVERSION FACTOR
2.1 Current Licensing Basis
The signal from a platinum fixed incore detector is predominantly from gamma
interaction with the platinum. A portion of the detector signal is from neutron interaction
with the platinum, predominantly the Pt-1 95 isotope. It was recognized in both the
topical report YAEC-1855PA and in the associated NRC SER dated 12/23/1993 that the
fraction of the total detector signal due to neutrons is approximate and not well known at
the time. Section 3 of YAEC-1855PA describes the assumptions used to determine an
estimate for the fraction of total detector signal due to neutrons. At that time, public
domain studies and a Seabrook specific sensitivity study based on operational data
were used to determine the estimate of the fraction neutron component to be used as
an input assumption in determining the predicted detector signal. Based on the
literature and the sensitivity study, a value of 25% of the total signal was attributed to
neutrons.
To accommodate the platinum detectors, SIMULATE-3 was modified, to allow the user
to input the fractional neutron component of the predicted detector signal. This fraction
is given in terms of the total detector signal, and it can be distributed by either or both
the fast and thermal neutron flux. The gamma portion of the detector's signal is
determined through the total responses determined in CASMO-3 cases and local
detector neutron flux calculations within SIMULATE-3. This is the standard method of
detector calculations used within SIMULATE-3. The total neutron portion of detector
signal is determined from the input fraction and is then distributed by the SIMULATE-3
calculated relative local thermal neutron flux levels at the detector locations. The
individual detector's gamma and neutron portions are then summed to determine the
detector's total signal.
As described in YAEC-1 855PA, a value of 0.25 was used for the thermal neutron
component of the predicted detector signal. Thus the total gamma signal was
calculated in SIMULATE-3 as:
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The above value of ST was used in FINC starting in Cycle 1.
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2.2 Proposed Method
To better cover a broader range of reactor core design and operating conditions, a new
formulation for determining the neutron component of the predicted detector signal was
developed. Rather than use the straight 25% of the gamma signal to represent the
neutron portion, it was determined that a more accurate representation of the total
signal could be accomplished by adding a neutron portion to the gamma signal based
on total neutron reaction rate. To do this, a new factor called the Neutron Conversion
Factor (NCF) was introduced. The new formulation using the neutron conversion factor
is shown in Equation 2.
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3.0 REPLACEMENT DETECTORS
3.1 General
The Seabrook specification for replacement detectors was written to produce a like-for-
like replacement of the original detectors. The replacement detectors were built to the
original specification and within the as-built attributes of the original detectors including
detector geometry, dielectric densities and component material impurities. The
replacement detectors were also constrained to the characteristics assumed in the
analysis software licensed for the system. These precautions served to preserve the
like-for-like nature of the replacement detectors to the original detector. Nonetheless,
the manufacturing enhancements developed in more than 20 years of detector service
result in differences in detector performance as observed in gamma testing of the
replacement detectors and archive original detectors.
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3.2 Current Licensing Basis
As described in YAEC-1855PA, the FINC code depends on the concept of a standard
detector. In the standard detector approach, the raw measured detector signals must
be corrected for individual detector differences. The signal from any individual detector
is a function of the incident flux, the amount of detector material and manufacturing
differences. Thus, each detector's signal must be modified to correspond to a signal
given by a standard detector. The standard detector is one built to exact design
dimensions. Since Cycle 1, each measured detector signal is corrected by a sensitivity
factor. The sensitivity factor is defined as the ratio of the detector surface area to the
surface area of a standard detector. The data required for the calculation of the
sensitivity factors is provided by the detector manufacturer's as-built data of detector
length and weight. The sensitivity factors for the replacement detectors were calculated
in the same manner as the original detectors in Cycle 1 using the as-built length and
weight. This feature in the current licensing basis has not changed. The sensitivity
factor is applied to the measured signal and is used to create a standard detector by
using the manufacturer's measured weight and length for each detector compared to
the weight and length of a standard detector.
3.3 Proposed Modification
The replacement detector specification required that each individual replacement
detector is tested for operation using a gamma source. In addition, to verify
compatibility, original archive detectors are tested in the same gamma source
environment. During the testing, it was noted that the replacement detectors produced
a lower signal than the original detectors in the same gamma field and could not be
corrected by application of the simple sensitivity factor based only on as-built detector
length and weight.
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The Gamma Correction Factor (GCF) was introduced in Cycle 14 to make the
replacement detector signal compatible with the signal from the original detectors. The
GCF is input to FINC as a simple multiplier on the measured signal for the replacement
detectors. Different values of the GCF are used for the Batch 1 and Batch 2
replacement detectors based on changes in the manufacturing process. As part of the
trending analysis, the GCF was refined through the trending analysis of Appendix A as
shown in Figure A-14, Figure A-15, and Figure A-16. The trending analysis compared
the difference in signal between the replacement detectors and their symmetric partners
over Cycles 14 and 15 for the Batch 1 replacement detectors and over Cycle 15 for the
Batch 2 replacement detectors. The GCF values reflect in-reactor measurements of
symmetric partners in the Seabrook reactor environment. The value of Batch 1 GCF is
1.0577 and the Batch 2 GCF is 1.0849. The Batch 2 replacement detectors defined the
future manufacturing process. It is the intent to use the Batch 2 GCF for future batches
of replacement detectors. However, since the magnitude of the detector signal can be
affected by the manufacturing process, future batches of detectors may require their
own GCF determined through testing.
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4.0
4.1
DEPLETION CORRECTION FACTOR
Current Licensing Basis
The current licensing basis does not include a depletion correction factor. The modeling
of the effects of elemental platinum depletion is not required as described in YAEC-
1855PA in response to RAI Question 4. [
] Thus, no provisions were provided in
the current licensing basis for a depletion correction.
4.2 Proposed Modification
] This effect is primarily due to
the consumption of the Pt-195 isotope which is the predominant contributor to the
neutron component of the total gamma signal of the detector.
From the trending analysis covering all 15 cycles, a linear Depletion Correction (DPC)
was derived in Appendix A as a function of detector exposure as shown in Figure A-1 1.
Detector exposure is the accumulated fuel exposure of the assembly containing the
detector, averaged over the detector length. With the proposed modification of FINC,
the DPC will be calculated for each detector based on detector exposures using the
derived curve. The DPC will be applied to each individual detector and will vary with
detector exposure. [
From Equation 3, the depletion correction factor utilizes the detector exposure to obtain
a multiplier to be applied to the measured signal for each detector.
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5.0 COMPARISON OF FINC RESULTS
5.1 General
With the completion of the trending analysis in Appendix A, the proposed modifications
to FINC were established. To determine the effect of these modifications on the
surveillance parameters, all 15 cycles of flux maps were rerun with the revised version
of FINC incorporating the proposed modifications. The 15 cycles provides a good test
of the proposed modifications to FINC under an array of operating conditions that
involved changes in fuel management strategy, changes in fuel design, power uprate,
normal core tilt condition and axial offset anomalies. The evaluation of the data is for
flux maps that were run under equilibrium conditions as would be the case for normal
surveillance.
5.2 Surveillance Parameter Comparisons
This section shows the comparison of the original FINC version to the modified FINC
version for the Tech Spec surveillance parameters. Although all 15 cycles of flux maps
were rerun with the modified version of FINC, comparisons are provided here for the
first eight cycles. During these cycles the licensing model used a fixed 25% of the
gamma signal as the neutron portion of the signal and did not include a correction for
detector exposure. The proposed modifications to FINC utilize a neutron conversion
factor and the neutron reaction rate to determine the neutron portion of the signal. The
proposed model also includes a correction for depletion based on the exposure of each
individual detector. The comparisons for the heat flux hot channel factor FQ are
provided in Figure 1 through Figure 8. The value of FQ includes the current
measurement uncertainty of 5.21% and the engineering heat flux uncertainty of 3%.
The comparisons for the enthalpy rise hot channel factor FAH are provided in Figure 9
through Figure 16 and the comparisons for axial offset are provided in Figure 17
through Figure 24. FAH values are shown without any uncertainty because the
uncertainty factor is applied to the limit, as specified in the core operating limits report.
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The results provided in Figure 1 through Figure 24 show that performance of the
proposed model compares well to the current licensing basis model. In these figures
the proposed model contains the neutron conversion factor, detector exposure tracking
and the depletion correction. The NCF was introduced in Cycle 9 in 2002 so that a
comparison to the original FINC version, consistent with the current licensing basis
methodology could not be made after Cycle 8.
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Figure 1 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 1
2.20 -
2.00 1
1.80 -
0E1.60. -
1.40 -
1.20 -
*Licensing Model OProposed Model1.00 -
0 2000 4000 6000 8000 10000 12000 14D00
Cyde Exposure (MWD/MTU)
Figure 2 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 2
1.95
1.90 -
1.85
EE: 1.80 [] 0
1.75 -00
1.75 -01.70
* Licensing Model O Proposed Model1.65
0 2000 4000 6000 8000 10000 12000
Cyde Exposure (MWD/MTU)
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Figure 3 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 3
2.00
1.95
00
1.90
E 0E1.85
1.80 -+
1.75 - 0
* Licensing Model OProposed Model1.70 1 1..
0 2000 4000 6000 8000 10000 12000 14000 16000
Cyde Exposure (MWD/MTU)
Figure 4 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 4
1.90
1.85
1.80
E 1.75
1.70
1.65
1.60
1.55
VPOD
100
0*Licensing Model OProposed Model
0 5000 10000
Cyde Exposure (MWD/MTU)
15000 20000
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Figure 5 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 5
2.00 ,
1.95 ___---__0___-__ _
1.90 [ 113 t 0
1.85 I=0
X 180 -
1.75o
1.70 -
* Licensing Model 0Proposed Model1.65 1 T
0 5000 10000 15000 200D0
Cyde Exposure (MWD/MIU)
Figure 6 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 6
2.05.
2.00
1.95
S1.90.
X 1.85
1.80
*Licensing Model OProposed Model
1.70 1 1 1
0 5000 10000 15000 20000 25000
Cyde Exposure (MWD/MTU)
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Figure 7 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 7
1.90
1.85
E
1.70
1.65
1 Licensing Model -0 Proposed Model1.60 ,,,
0 5000 10000 15000 20D00
Cycle Exposure (MWD/MTU)
Figure 8 Comparison of Heat Flux Hot Channel Factor FQ for Cycle 8
1.90
1.88
1.86
1.84
•o1.82E
E 1.80
• 1.78
1.76
1.74
1.72
1.70
200000 5000 100O0 15000
Cycle Exposure (MWD/MTU)
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Figure 9 Comparison of Enthalpy Rise Hot Channel Factor FAH forCycle I
1.40
1.38
1.36
1.3413
E 1.32
91.30
1.28
1.26
1.24
p
0*
0 0
* Licensing Model 0'Proposed Model
0 2000 4000 6000 8000 10000
Cyde Exposure (MWD/MTU)
12000 14000
Figure 10 Comparison of Enthalpy Rise Hot Channel Factor FAH forCycle 2
1.46
[0 D
1.44
1.42 -
= 1.40
1.38
1.36
#Licensing Model r-Proposed Model
1.34 - I
0 5000 10000 150D0 20000
Cyde Exposure (MWD/MTU)
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Figure 11 Comparison of Enthalpy Rise Hot Channel Factor FAH forCycle 3
1.46
+0 0 001.45 0 0
0*
E_E1.43
1.42 -
1.41
*Licensing Model OProposed Model1.40 .......
0 2000 4000 6000 8000 10000 12000 14000 16000
Cyde Exposure (MWD/MTU)
Figure 12 Comparison of Enthalpy Rise Hot Channel Factor FAH for
Cycle 4
1.46
n n
1.44
i*1.42
1.40
1.38
1.36
*Licensing Model OProposed Model I
1.34 - I
0 5000 10000 15000 20000
Cyde Exposure (MWD/MTU)
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Figure 13 Comparison of Enthalpy Rise Hot Channel Factor FAH forCycle 5
1.49
1.48
1.47
1.46
U' 1.45_E1.44
1.43
o
n r0p
*Licensing Model n Proposed Model
1.42
1.41
1.40
0 5000 10000
Cycle Exposure (MWD/MTU)
15000 20000
Figure 14 Comparison of Enthalpy Rise Hot Channel Factor FAH forCycle 6
1.561.54
1.52 A 17
1E 5
x 1.48
1.46- i_
1.44 ,
1.42 Licensing Model OProposed Model
0 5000 10000 15000 20000 25000
Clyde Exposure (MWD/MTU)
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Figure 15 Comparison of Enthalpy Rise Hot Channel Factor FAH forCycle 7
1.45
1.44
1.43
1.42
E 1.41
E OS1.40
1.39
1.38
1.37
1.360 5000 10000 15000 2000O
Cyde Exposure (MWD/MTU)
Figure 16 Comparison of Enthalpy Rise Hot Channel Factor FAH forCycle 8
1.44
144
1.43
1.431
E1.42~ 00
1.40 -
1.39 -
1.9 #Licensing Mode 1 0Proposed ModelI
0 5000 10000 15000 20000
Cycle Exposure (MWD/MTU)
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Figure 17 Comparison of Axial Offset for Cycle 1
0.0
-1.0
-2.0
-- 3.0
Z -4.0
950
-6.0
-7.0
-8.0
-9.0
O [.* 00
*0 0
0
*Licensing Model OProposed Model
2000i 100 120 40
0 200D 4000 6000 8000
CYde Exposure (MWD/MTU)
10000 120D0 14000
6.0
5.0
4.0
3.0
2.0
1.0
0.0
-1.0
-2.0
-3.0
-4.0
Figure 18 Comparison of Axial Offset for Cycle 2
0
.,0 [
0 *
0 P * de
*Licensing Model OProposed Model
0 2000 4000 6000 8000
Cycle Exposure (MWD/MT1)
10000 12000
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Figure 19 Comparison of Axial Offset for Cycle 3
0.0-
-0.5
-1.0- 13. . 0
_9-2.0- A
•-2.5 -+q •
S0 •-3.0 B-0
-3.5
- Licensing Model 0 Proposed Model-4.0-
0 2000 4000 6000 8000 10000 12000 14000 16000
Cyde Exposure (MWD/MTU)
1-46
1.44
1.42
E_E 1.40
1.38
Figure 20 Comparison of Axial Offset for Cycle 4
0* *0 0
0 +
#• Licensing Model OProposed Model I 1
*
1.36
1.34
0 5000 10000
Cyde Exposure (MWD/MTU)
15000 20000
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Figure 21 Comparison of Axial Offset for Cycle 5
3
2.0
1.0
0.0
-1.0
-2.0
-3.0
-4.0
-5.0
-6.0
*Licensing Model 0 Proposed Model "0
-- ~J-5 0w 0~ ,d
0[ED .*+ ,, n o O
0 5000 10000
Cyde Exposure (MWD/MTU)
15000 20000
4.0
3.0
2.0
1.0
0.0
-1.0
-2.0.2.1
Figure 22 Comparison of Axial Offset for Cycle 6
4,,5A.- FI
I I ~cen~ng odi ropoedM~iA
-3.0
-4.0
-5.0
-6.00 5000 10000 15000 20000 25000
Cyde Exposure (MWD/MTU)
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Figure 23 Comparison of Axial Offset for Cycle 7
4.0 -
3.0-
2.0-
1.0 *Licensing Model 0 Proposed Model +0
-3.0
-4.0
-5.00 5000 10000 15000 20000
Cyde Exposure (MWO/MTU)
Figure 24 Comparison of Axial Offset for Cycle 8
0.0
-0.5
-1.0
1. 5.5
I -2.0
,• -2.5
-3.0
-3.5
-4.0
0 5000 10000 15000
Cyde Exposure (MWD/MnU)
20000
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5.3 Statistical Results
With the proposed modifications, a new uncertainty analysis was performed that better
represents the true measurement uncertainty for FQ and FAH over a wide range of
conditions by propagating the uncertainties through the FIDS analysis system using a
Monte Carlo statistical simulation method. This statistical simulation method replaces
the signal reproducibility and detector processing uncertainty terms in the YAEC-
1855PA uncertainty analysis. [
] The
results of the simulation analysis were statistically combined with the Analytical Methods
and Axial Signal Power Shape uncertainty terms from YAEC-1855PA, which remained
unchanged, and determined a total measurement uncertainty of the FIDS analysis
system of less than 4.0% for FAH and less than 5% for FQ.
The accuracy and functionality of the FIDS analysis system remains comparable to the
original YAEC-1855PA analysis and the Moveable Incore Detector System.
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6.0 UNCERTAINTY ANALYSIS
6.1 Current Licensing Basis
As noted in YAEC-1 855PA, the uncertainty of the fixed incore detector system is
addressed in four individual parts. Each of these parts are quantified and then
statistically combined to achieve a total system uncertainty at a 95/95 confidence level
with a one-sided tolerance limit. The uncertainties associated with FAH and FQ have
traditionally been treated independently. The uncertainty in the three-dimensional
parameter FQ contains all axial and radial components of the system uncertainty.
However, the two-dimensional parameter FAH is an axially integrated quantity that does
not contain the axial uncertainty component. Uncertainties for each of these quantities
are defined independently below.
The total system uncertainty applied to the three-dimensional quantity of FQ defined as:
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The second uncertainty factor is applied to the two-dimensional axially integrated
quantity of FAH. The radial or FAH uncertainty requires the combination of three of the
four uncertainty components. The axial power shape uncertainty does not apply to the
integrated radial parameters and the radial detector processing uncertainty contains
only the axially integrated processing component. The system two-dimensional
uncertainty, as applied to FAH, is defined as:
The 95/95 confidence level with a one-sided tolerance limit can be calculated from the
standard deviation for each component and the appropriate confidence level multiplier.
The confidence level multiplier (k) is directly dependent on the size of the data set and
was determined from Reference 4. For reference, the components and confidence
factors from YAEC-1 855PA are provided in Table 1 below.
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Table I Uncertainty Components and Confidence Multipliers fromYAEC-1855PA
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6.2 Proposed Uncertainty Modifications
6.2.1 Overview
A new uncertainty analysis was performed that better represents the true measurement
uncertainty for FQ and FAH over a wide range of conditions by propagating the
uncertainties through the FIDS analysis system using a Monte Carlo statistical
simulation method. This statistical simulation method replaces the signal reproducibility
(aa), and detector processing (Gd and Ge) uncertainty terms in the YAEC-1855PA
uncertainty analysis.
The FIDS analysis system is statistical in nature. Consequently, the determination of
the measured peaking factor is affected by detector measurement variability, the
number and layout of available detectors, signal replacement techniques, expansion of
the measured power to uninstrumented core locations, and any differences between
predicted and true power distribution. Accordingly, a range of conditions need to be
considered in determination of the system uncertainty. For this reason the FIDS
analysis system uncertainty has been determined using the Monte Carlo statistical
simulation method in which [
] The FIDS analysis system determines the measured power
distribution FAH and FQ surveillance parameters from these simulated detector signals
using the power distribution processing methodology described in Section 4.0 of YAEC-
1855PA, including the proposed modifications described in Sections 2.2, 3.3, and 4.2 of
this document. In the simulation, a range of detector failures is considered in
combination with a range of perturbations between the predicted and true power
distribution.
This uncertainty analysis methodology is similar to that employed by the Reference 5
and 6 core power distribution monitoring systems previously reviewed and approved by
the NRC.
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6.2.2 Methodology
The FIDS analysis system contains two major software components: FINC and
SIMULATE-3. In normal core monitoring, SIMULATE-3 provides the predicted detector
signals and a predicted power distribution. FINC uses the measured and predicted
detector signals to adjust the predicted power distribution to produce the measured
power distribution. This algorithm is described in YAEC-1855PA, Section 4.4.
For the uncertainty calculation, [
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] The uncertainty factors for
Analytical Methods and Axial Signal Power Shape (ob and Oc in Equations 7 and 8 of
YAEC-1855PA) are retained because those effects cannot be analyzed by this
uncertainty methodology.
FQ UL(95/95) and FAH UL(95/95) are also computed with an equivalent non-parametric
method that does not assume the distributions are normal. [
[
I
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Figure 25 Flow Diagram of Calculations
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6.2.3 Uncertainty Calculation Details
6.2.3.1 Physics Analytical Methods Uncertainty
The CASMO-3 and SIMULATE-3 code package used to generate all analytical
predictions for power distribution related parameters has not changed since the initial
licensing analysis in YAEC-1855PA. Since the physics analysis methods have not
changed, the analytical methods uncertainty, 0 b, has not changed
6.2.3.2 Axial Power Shape Uncertainty
As noted in YAEC-1855PA, the axial profiles calculated by SIMULATE-3 are the basis
for determining the measured axial power shapes from the fixed detector data within the
core. Measured axial power distributions are determined from the fixed incore detector
signals and from the detailed axial power shapes generated by the SIMULATE-3
analytical model. Since the SIMULATE-3 methodology has not changed, the axial
power shape uncertainty, ao, has not changed.
6.2.3.3 Simulation Uncertainty Analysis
6.2.3.3.1 Operating State Points
Three operating state points were chosen for the uncertainty analysis:
* Cycle 14, cycle exposure where FNH is near the maximum, excluding the beginning
of cycle non-equilibrium cases.
* Cycle 14, cycle exposure where FQ is near the maximum, excluding the beginning of
cycle non-equilibrium cases.
* Cycle 13, cycle exposure where axial offset is near minimum (largest negative value)
and the Axial Offset mismatch is also near maximum.
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6.2.3.3.2 Perturbations in Measured Power Distributions
6.2.3.3.3 Detector Signal Variance
Detector signal variance consists of reproducibility of detector responses, uncertainty in
plant parameter measurements, variability in reactor conditions, uncertainty in detector
sensitivity corrections (including sensitivity, gamma, and depletion corrections), and
uncertainty in the detector predictive model. [
I
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6.2.4 Uncertainty Calculation Results
Three reactor operating state points were analyzed. [
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XlP-3243NPRevision 1
Paae 41Licensinn Report Paoe 41
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6.2.5 Analysis of Significant Trends
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Table 2 95/95 Uncertainty Limits for FAH and FQ
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Figure 26 FAH UL(95/95) Plots for Cycle 14, FAH Near Maximum
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Figure 27 FQ UL(95/95) Plots for Cycle 14, FAH Near Maximum
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7.0 CONCLUSIONS
The information provided here to supplement YAEC-1 855PA shows the modifications
made to the FINC code to improve the accuracy and accommodate replacement
detectors consistent with the concept of the standard detector as noted in YAEC-
1855PA. The modifications to FINC utilize the information determined from an
extensive trending program to analyze the first 15 cycles of operation of Seabrook. The
rerun of 15 cycles of flux maps showed detector performance data Which provides
confidence in the proposed method of analysis.
The current licensing basis uncertainty analysis methodology is replaced with a new
methodology that determines the true measurement uncertainty for FQ and FAH. These
uncertainties are specific to the analytical physics methods, CASMO-3 and SIMULATE-
3 and the incore data processing code, FINC, and the general design of the platinum
fixed detectors for Seabrook Station. Conservatively bounding measurement
uncertainty values of 4.0% for FAH and 5.0% for FQ for the FIDS analysis methodology
are proposed. These are slightly higher than the values supported by the uncertainty
analysis and are consistent with the Moveable Incore Detector System (MIDS).
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8.0 REFERENCES
1. Joseph P. Gorski, "Seabrook Station Unit 1 Fixed Incore Detector System
Analysis," YAEC-1855PA, October 1992.
2. M. Edenius and Bengt-Herman Forssen, "CASMO-3: A Fuel Assembly
Burnup Program, User's Manual," STUDSVIK/NFA-89/3, January 1991.
3. K.S. Smith, K.R. Rempe and D.M. VerPlanck, "SIMULATE-3: Advanced
Three-Dimensional Two-Group Reactor Analysis Code, Methodology,"
STUDSVIK/NFA-89-04, November 1989.
4. D.B. Owen, Factors for One-Sided Tolerance Limits and for Variables
Sampling Plans, SCR607, US Dept. of Commerce, March 1963.
5. R. Kochendarfer, "Statistical Universal Power Reconstruction with Fixed
Margin Technical Specifications," ANP-1 0301 P-A. AREVA, Inc.,
September 2013.
6. R. Kochendarfer, C. T. Rombaugh and A.Y. Cheng, Fixed Margin
Technical Specifications," BAW-10158P-A. Babcock and Wilcox, August
1986.
7. Carl A. Bennett and Normal L. Franklin, "Statistical Analysis in Chemistry
and the Chemical Industry", John Wiley & Sons, New York, 1954.
8. Gerald J. Hahn and Samuel Shapiro, "Statistical Models in Engineering",
John Wiley & Sons Inc., New York, 1967.
9. Mary Gibbons Natrella, "Experimental Statistics", National Bureau of
Standards", 1963.
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APPENDIX A
The trending analysis processed the measured signal data for 15 cycles of Seabrook
operation. The trending analysis used the calculation sequence of cross section
generation by CASMO-3, power prediction generation by SIMULATE-3 and measured
data processed by FINC. The CASMO-3 and SIMULATE-3 codes are the same
versions used in YAEC-1855PA and have not changed. The trending analysis
contained the use of the Neutron Conversion Factor (NCF) that was introduced in
Cycle 9.
CASMO-3 provides the cross section input and gamma response to SIMULATE-3. The
power distribution predictions, predicted gamma signal, and neutron reaction rate are
produced by SIMULATE-3. For the trending analysis, the data extracted from
SIMULATE-3 was the three dimensional power distributions, the detector gamma signal
and the nodal neutron reaction rate for platinum. FINC processed the measured signals
correcting for the surface area to obtain results for a standard detector.
Post processing software and Excel spreadsheets were used to analyze the data. The
following pieces of data were used in the trending analysis:
" The measured signal, SM, from FINC corrected for surface area to correct to a
standard detector.
* The predicted gamma signal, SG, for the five detector levels came from SIMULATE-3
without modification.
" The detector neutron reaction rate came from the 3D predicted nodal neutron
reaction rate for platinum from SIMULATE-3 and collapsed by the post processing
software over the detector length and axial location to obtain Rn.
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" Detector power was generated by the post processing software from the 3D nodal
assembly power fraction from SIMULATE-3. The nodal assembly power fraction
was collapsed over the detector length and axial location to generate a detector
power in megawatts.
* Detector exposure was generated by the post processing software from the 3D
nodal assembly exposure from SIMULATE-3. The nodal assembly exposure was
collapsed over the detector length and axial location to generate a detector exposure
in GWD/MTU. The detector exposure was accumulated to be current for each flux
map.
* A power independent measured detector signal was generated by the post
processing software by dividing the measured signal, SM, by the detector power.
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The trending analysis is based on 15 cycles of Seabrook operation as summarized
below:
* Seabrook contains 58 detector strings with 5 detectors per string.
* The 15 cycles comprise 813 reactor flux maps.
" Failed detectors or detector strings were removed, i.e., no signal produced.
" The analysis considered only original detectors for the determination of the NCF and
DPC. Replacement detectors were incorporated into the figures to show
consistency.
* This resulted in 221,226 unique data points.
" A total of 145 anomalous flux maps were removed. Non-equilibrium flux maps and
flux maps with an axial offset anomaly were removed in order to obtain a good
estimate of the NCF and DPC parameters. A total of 145 flux maps were removed.
* The result was that 180,393 unique data points were used in the trending analysis.
The results of the trending analysis are provided in Figure A-1 through Figure A-16.
The trending analysis for the original detectors is over all 15 cycles while the trending
for the replacement detectors is over Cycle 14 and 15 for the Batch 1 replacement
detectors and Cycle 15 for the Batch 2. replacement detectors. Where applicable, the
figures show a linear fit through the data as a solid black line.
Figure A-1 shows the measured signal (SM) divided by the detector power versus
detector exposure for the original detectors. Figure A-2 shows the measured signal
divided by the detector power versus detector exposure for the replacement detectors.
The overall trend shows a decrease in signal as a function of detector exposure for both
the original and replacement detectors. The trend shows changes due to changes in
neutron and gamma spectrum during cycle burnup; changes from cycle to cycle due to
core design and operating conditions; and changes due detector depletion.
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Figure A-3 shows the calculated gamma signal (Cy*SG from Equation 2 in Section 2.2)
divided by the detector power versus detector exposure for the original detectors.
Figure A-4 shows the calculated gamma signal divided by the detector power versus
detector exposure for the for the replacement detectors. The overall trend shows a
decrease in the calculated gamma signal as a function of detector exposure for both the
original and replacement detectors. The trend shows that the predictive model captures
the effect of changes during the cycle, changes in core design and fuel management
strategy and changes in operation conditions. The predictive model does not account
for detector depletion.
Figure A-5 shows the inferred neutron signal [ ] divided by the detector
power versus detector exposure for the original detectors. The overall trend shows a
decrease in the inferred neutron signal as a function of detector exposure. Figure A-6
shows the inferred neutron signal divided by the detector power versus detector
exposure for the replacement detectors. Due to the short exposure time and the small
number of replacement detectors, the overall trend shows no discernible decrease in
the inferred neutron signal as a function of detector exposure.
To isolate the effect of detector depletion, the Neutron Conversion Factor (NCF)
calculated from Equation 6 is used. Figure A-7 shows the NCF versus detector
exposure for the original detectors. The overall trend shows very slight decrease in the
NCF as a function of detector exposure. From this data a linear relationship for the
NCF was determined as NCF = A + B*E where E is the detector exposure in GWD/MTU
and A and B are the constants of the linear equation. For comparison, Figure A-8
shows the NCF versus detector exposure for the for the replacement detectors. Again,
due to the short exposure and the small number of replacement detectors, the overall
trend shows no discernible decrease or increase in the NCF as a function of detector
exposure. It should be noted that the NCF for all detectors is derived from the original
detectors only. Figure A-8 is intended to show the similarity in NCF between original
and replacement detectors.
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Figure A-9 shows the calculated gamma signal divided by the measured signal as a
function of detector exposure for the original detectors. From this figure it is clear that
the gamma portion of the signal has been approximately 75% of the total signal. The
refinement made in Cycle 9 to use the NCF rather than a straight 25% of the gamma
portion of the signal more accurately represents the change in the neutron portion of the
signal with changing core conditions. Figure A-10 shows the calculated gamma signal
divided by the measured signal as a function of detector exposure for the replacement
detectors. The trend of the replacement detectors appears to be consistent with that of
the original detectors.
From the 15 cycles of trend data, there are observed trends in the measured signal, the
calculated gamma signal, and the inferred neutron signal. [
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Figure A-12 shows the difference between the predicted and measured signals for the
original detectors using the proposed model. This figure shows there is no trend in the
data with exposure and provides a basis for the proposed model.
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Replacement detector strings were installed in Cycle 14 (Batch 1) and Cycle 15
(Batch 2). The replacement detectors were constructed to be similar to the original
detectors, but are slightly less sensitive than the original detectors due primarily to
changes in the manufacturing process. The change in sensitivity was noted and the
FINC code was modified to introduce a batch dependent Gamma Correction Factor. As
part of the trending analysis, the change in the Batch 1 and Batch 2 sensitivity was
refined by comparing the measured signal from the replacement detectors to their
symmetric partners of original detectors. The detector signals were corrected for
depletion effects using the DPC from above. The comparisons are shown graphically in
Figure A-14 and Figure A-15 for the Batch 1 detectors and in Figure A-16 for the Batch
2 detectors.
Figure A-1 3 shows the difference between the predicted and measured signals for the
replacement detectors using the proposed model with the Gamma Correction Factor.
This figure shows there is no trend in the data with exposure but a small bias. Since the
bias is small, this provides a basis for the proposed model with the replacement
detectors.
Using the approach of comparing to symmetric partners, the Gamma Correction Factor
(GCF) is computed as:
Equation 11 GCF = Signal from Original Detector * DPC
Signal from Replacement Detector * DPC
Gamma Correction Factor for the replacement detectors is provided by detector batch
and the GCF for Batch 1 is 1.0577 and the GCF for Batch 2 is 1.0849. These values
with be input to FINC as constants to be applied to the Batch 1 and Batch 2 measured
signals as simple multipliers.
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Figure A-1 Measured Signal Divided by Detector Power versus Detector Exposure, Original Detectors
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Figure A-2 Measured Signal Divided by Detector Power versus Detector Exposure, Replacement Detectors -
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Figure A-3 Calculated Gamma Signal Divided by Detector Power versus Detector Exposure, Original Detectors
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- Figure A-4 Calculated Gamma Signal Divided by Detector Power versus Detector Exposure, Replacement Detectqor
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Figure A-5 Inferred Neutron Signal Divided by Detector Power versus Detector Exposure, Original Detectors
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-Figure A-6 Inferred Neutron Signal Divided by Detector Power versus Detector Exposure, Replacement Detectors
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Figure A-7 Neutron Conversion Factor versus Detector Exposure, Original Detectors
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Figure A-8 Neutron Conversion Factor versus Detector Exposure, Replacement Detectors
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Figure A-9 Calculated Gamma Divided by Measured Signal versus Detector Exposure, Original Detectors
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Figure A-10 Calculated Gamma Divided by Measured Signal versus Detector Exposure, Replacement Detectors
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Figure A-11 Depletion Correction Factor
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Figure A-12 Difference between Predicted and Measured Signals, Original Detectors, Proposed Model
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Figure A-1 3 Difference between Predicted and Measured Signals, Replacement Detectors, Proposed Model
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Figure A-14 Ratio of Measured Signals for Original to Replacement Detectors, Batch 1, Cycle 14
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Figure A-15 Ratio of Measured Signals for Original to Replacement Detectors, Batch 1, Cycle 15 -
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- Figure A-16 Ratio of Measured Signals for Original to Replacement Detectors, Batch 2, Cycle 15
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APPENDIX B
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AREVA Inc. A
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4P-3243NPRevision 1
Paqe 75
Table B-1 Conservative Trend Slope of FAH UL(95/95) and FQUL(95/95) for a Maximum of 8 Failed Detector Strings
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Figure B-1 Example Linear Least Square Fits of FAH (UL 95/95) and FQ(UL 95/95)